Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells19133
Missing cells (%)12.8%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory1.3 MiB
Average record size in memory133.0 B

Variable types

Categorical4
Text5
Numeric6

Dataset

Description등록신청사업,영업구분,등록증번호,상호,법인여부,사업장 전화번호,소재지,소재지(도로명),우편번호,등록일자,유효기간만료일자,폐쇄일자,지점설립일자,본점여부,최근수정일자
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-11482/S/1/datasetView.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
등록일자 is highly overall correlated with 유효기간만료일자 and 3 other fieldsHigh correlation
유효기간만료일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
폐쇄일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
지점설립일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
최근수정일자 is highly overall correlated with 등록일자 and 3 other fieldsHigh correlation
본점여부 is highly imbalanced (93.8%)Imbalance
등록증번호 has 166 (1.7%) missing valuesMissing
사업장 전화번호 has 3412 (34.1%) missing valuesMissing
소재지 has 298 (3.0%) missing valuesMissing
소재지(도로명) has 4814 (48.1%) missing valuesMissing
우편번호 has 5576 (55.8%) missing valuesMissing
유효기간만료일자 has 2027 (20.3%) missing valuesMissing
폐쇄일자 has 1594 (15.9%) missing valuesMissing
지점설립일자 has 1246 (12.5%) missing valuesMissing

Reproduction

Analysis started2024-05-11 06:46:33.804360
Analysis finished2024-05-11 06:47:41.130507
Duration1 minute and 7.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대부업
6230 
대부중개업
3359 
<NA>
 
411

Length

Max length5
Median length3
Mean length3.7129
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대부업
2nd row대부업
3rd row대부업
4th row대부중개업
5th row대부중개업

Common Values

ValueCountFrequency (%)
대부업 6230
62.3%
대부중개업 3359
33.6%
<NA> 411
 
4.1%

Length

2024-05-11T15:47:41.248724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:41.402755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 6230
62.3%
대부중개업 3359
33.6%
na 411
 
4.1%

영업구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
3720 
<NA>
2936 
타시군구이관
1195 
영업중
827 
유효기간만료
807 
Other values (2)
515 

Length

Max length6
Median length4
Mean length3.5743
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row유효기간만료
4th row<NA>
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 3720
37.2%
<NA> 2936
29.4%
타시군구이관 1195
 
11.9%
영업중 827
 
8.3%
유효기간만료 807
 
8.1%
직권취소 512
 
5.1%
갱신등록불가 3
 
< 0.1%

Length

2024-05-11T15:47:41.547652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:41.777638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3720
37.2%
na 2936
29.4%
타시군구이관 1195
 
11.9%
영업중 827
 
8.3%
유효기간만료 807
 
8.1%
직권취소 512
 
5.1%
갱신등록불가 3
 
< 0.1%

등록증번호
Text

MISSING 

Distinct9804
Distinct (%)99.7%
Missing166
Missing (%)1.7%
Memory size156.2 KiB
2024-05-11T15:47:42.105196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length19.50122
Min length1

Characters and Unicode

Total characters191775
Distinct characters67
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9775 ?
Unique (%)99.4%

Sample

1st row2010-서울강남-0422
2nd row2007-서울특별시-01327(대부업)
3rd row2018-서울성동-022(대부업)
4th row2008-서울특별시-01752(대부중개업)
5th row2013-서울구로-018(대부중개업)
ValueCountFrequency (%)
2012-서울특별시 16
 
0.2%
2010-서울 14
 
0.1%
2011-서울특별시 14
 
0.1%
2013-서울특별시 13
 
0.1%
2014-서울특별시 11
 
0.1%
2015-서울특별시 10
 
0.1%
2016-서울특별시 10
 
0.1%
대부업 8
 
0.1%
2017-서울특별시 7
 
0.1%
대부중개업 7
 
0.1%
Other values (9768) 9861
98.9%
2024-05-11T15:47:42.582866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33927
17.7%
- 19653
 
10.2%
2 15767
 
8.2%
1 11909
 
6.2%
10935
 
5.7%
9809
 
5.1%
8474
 
4.4%
( 8217
 
4.3%
8176
 
4.3%
) 8150
 
4.2%
Other values (57) 56758
29.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82682
43.1%
Other Letter 72936
38.0%
Dash Punctuation 19653
 
10.2%
Open Punctuation 8217
 
4.3%
Close Punctuation 8150
 
4.2%
Space Separator 137
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10935
15.0%
9809
13.4%
8474
11.6%
8176
11.2%
7936
10.9%
3472
 
4.8%
2886
 
4.0%
2495
 
3.4%
2487
 
3.4%
2486
 
3.4%
Other values (43) 13780
18.9%
Decimal Number
ValueCountFrequency (%)
0 33927
41.0%
2 15767
19.1%
1 11909
 
14.4%
3 3688
 
4.5%
8 3095
 
3.7%
4 3056
 
3.7%
9 2827
 
3.4%
5 2822
 
3.4%
6 2806
 
3.4%
7 2785
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 19653
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8217
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8150
100.0%
Space Separator
ValueCountFrequency (%)
137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118839
62.0%
Hangul 72936
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10935
15.0%
9809
13.4%
8474
11.6%
8176
11.2%
7936
10.9%
3472
 
4.8%
2886
 
4.0%
2495
 
3.4%
2487
 
3.4%
2486
 
3.4%
Other values (43) 13780
18.9%
Common
ValueCountFrequency (%)
0 33927
28.5%
- 19653
16.5%
2 15767
13.3%
1 11909
 
10.0%
( 8217
 
6.9%
) 8150
 
6.9%
3 3688
 
3.1%
8 3095
 
2.6%
4 3056
 
2.6%
9 2827
 
2.4%
Other values (4) 8550
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118839
62.0%
Hangul 72936
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33927
28.5%
- 19653
16.5%
2 15767
13.3%
1 11909
 
10.0%
( 8217
 
6.9%
) 8150
 
6.9%
3 3688
 
3.1%
8 3095
 
2.6%
4 3056
 
2.6%
9 2827
 
2.4%
Other values (4) 8550
 
7.2%
Hangul
ValueCountFrequency (%)
10935
15.0%
9809
13.4%
8474
11.6%
8176
11.2%
7936
10.9%
3472
 
4.8%
2886
 
4.0%
2495
 
3.4%
2487
 
3.4%
2486
 
3.4%
Other values (43) 13780
18.9%

상호
Text

Distinct8709
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:47:42.994176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length7.7542
Min length1

Characters and Unicode

Total characters77542
Distinct characters777
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7652 ?
Unique (%)76.5%

Sample

1st row디비에스대부 유한회사
2nd row성지대부
3rd row한울타리대부
4th row신성캐피탈
5th row새빛금융대부
ValueCountFrequency (%)
주식회사 831
 
7.0%
대부 302
 
2.5%
대부중개 295
 
2.5%
유한회사 64
 
0.5%
캐피탈 21
 
0.2%
대부업 15
 
0.1%
전당포 13
 
0.1%
money 11
 
0.1%
10
 
0.1%
loan 10
 
0.1%
Other values (8720) 10338
86.8%
2024-05-11T15:47:43.638983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8541
 
11.0%
8169
 
10.5%
2756
 
3.6%
2280
 
2.9%
2082
 
2.7%
2054
 
2.6%
1941
 
2.5%
) 1938
 
2.5%
( 1927
 
2.5%
1915
 
2.5%
Other values (767) 43939
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67837
87.5%
Uppercase Letter 2260
 
2.9%
Close Punctuation 1938
 
2.5%
Open Punctuation 1927
 
2.5%
Space Separator 1915
 
2.5%
Lowercase Letter 1113
 
1.4%
Decimal Number 272
 
0.4%
Other Punctuation 234
 
0.3%
Dash Punctuation 30
 
< 0.1%
Other Symbol 11
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8541
 
12.6%
8169
 
12.0%
2756
 
4.1%
2280
 
3.4%
2082
 
3.1%
2054
 
3.0%
1941
 
2.9%
1371
 
2.0%
1124
 
1.7%
1051
 
1.5%
Other values (691) 36468
53.8%
Uppercase Letter
ValueCountFrequency (%)
S 311
13.8%
K 209
 
9.2%
J 193
 
8.5%
C 187
 
8.3%
M 174
 
7.7%
H 142
 
6.3%
D 91
 
4.0%
B 85
 
3.8%
L 84
 
3.7%
G 83
 
3.7%
Other values (16) 701
31.0%
Lowercase Letter
ValueCountFrequency (%)
e 149
13.4%
n 132
11.9%
o 111
10.0%
a 107
 
9.6%
i 68
 
6.1%
s 65
 
5.8%
t 64
 
5.8%
c 54
 
4.9%
r 48
 
4.3%
m 46
 
4.1%
Other values (15) 269
24.2%
Decimal Number
ValueCountFrequency (%)
1 89
32.7%
2 42
15.4%
4 34
 
12.5%
9 24
 
8.8%
3 21
 
7.7%
5 21
 
7.7%
6 18
 
6.6%
7 10
 
3.7%
0 8
 
2.9%
8 5
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 125
53.4%
& 92
39.3%
? 7
 
3.0%
, 5
 
2.1%
* 2
 
0.9%
1
 
0.4%
' 1
 
0.4%
/ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 1938
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1927
100.0%
Space Separator
ValueCountFrequency (%)
1915
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Other Symbol
ValueCountFrequency (%)
11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67830
87.5%
Common 6320
 
8.2%
Latin 3374
 
4.4%
Han 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8541
 
12.6%
8169
 
12.0%
2756
 
4.1%
2280
 
3.4%
2082
 
3.1%
2054
 
3.0%
1941
 
2.9%
1371
 
2.0%
1124
 
1.7%
1051
 
1.5%
Other values (674) 36461
53.8%
Latin
ValueCountFrequency (%)
S 311
 
9.2%
K 209
 
6.2%
J 193
 
5.7%
C 187
 
5.5%
M 174
 
5.2%
e 149
 
4.4%
H 142
 
4.2%
n 132
 
3.9%
o 111
 
3.3%
a 107
 
3.2%
Other values (42) 1659
49.2%
Common
ValueCountFrequency (%)
) 1938
30.7%
( 1927
30.5%
1915
30.3%
. 125
 
2.0%
& 92
 
1.5%
1 89
 
1.4%
2 42
 
0.7%
4 34
 
0.5%
- 30
 
0.5%
9 24
 
0.4%
Other values (13) 104
 
1.6%
Han
ValueCountFrequency (%)
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (8) 8
44.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67818
87.5%
ASCII 9692
 
12.5%
CJK 18
 
< 0.1%
None 12
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8541
 
12.6%
8169
 
12.0%
2756
 
4.1%
2280
 
3.4%
2082
 
3.1%
2054
 
3.0%
1941
 
2.9%
1371
 
2.0%
1124
 
1.7%
1051
 
1.5%
Other values (672) 36449
53.7%
ASCII
ValueCountFrequency (%)
) 1938
20.0%
( 1927
19.9%
1915
19.8%
S 311
 
3.2%
K 209
 
2.2%
J 193
 
2.0%
C 187
 
1.9%
M 174
 
1.8%
e 149
 
1.5%
H 142
 
1.5%
Other values (63) 2547
26.3%
None
ValueCountFrequency (%)
11
91.7%
1
 
8.3%
CJK
ValueCountFrequency (%)
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (8) 8
44.4%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

법인여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7111 
법인
2889 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row법인
2nd row개인
3rd row개인
4th row개인
5th row개인

Common Values

ValueCountFrequency (%)
개인 7111
71.1%
법인 2889
28.9%

Length

2024-05-11T15:47:43.855505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:44.000589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7111
71.1%
법인 2889
28.9%
Distinct5807
Distinct (%)88.1%
Missing3412
Missing (%)34.1%
Memory size156.2 KiB
2024-05-11T15:47:44.328849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length40
Mean length10.620219
Min length1

Characters and Unicode

Total characters69966
Distinct characters38
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5188 ?
Unique (%)78.7%

Sample

1st row07082465607
2nd row025392063
3rd row02-466-7706
4th row02 948 1101
5th row.
ValueCountFrequency (%)
02 297
 
4.0%
76
 
1.0%
070 34
 
0.5%
010 10
 
0.1%
1688 7
 
0.1%
2212 6
 
0.1%
02-737-2882 6
 
0.1%
2209 6
 
0.1%
1566 5
 
0.1%
1644 5
 
0.1%
Other values (6114) 6967
93.9%
2024-05-11T15:47:44.855286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11402
16.3%
2 10153
14.5%
- 7051
10.1%
5 5955
8.5%
7 5465
7.8%
1 5057
7.2%
3 4969
7.1%
6 4946
7.1%
8 4835
6.9%
4 4815
6.9%
Other values (28) 5318
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61639
88.1%
Dash Punctuation 7051
 
10.1%
Space Separator 940
 
1.3%
Other Punctuation 186
 
0.3%
Close Punctuation 70
 
0.1%
Math Symbol 30
 
< 0.1%
Open Punctuation 27
 
< 0.1%
Other Letter 20
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
15.0%
3
15.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (6) 6
30.0%
Decimal Number
ValueCountFrequency (%)
0 11402
18.5%
2 10153
16.5%
5 5955
9.7%
7 5465
8.9%
1 5057
8.2%
3 4969
8.1%
6 4946
8.0%
8 4835
7.8%
4 4815
7.8%
9 4042
 
6.6%
Other Punctuation
ValueCountFrequency (%)
* 108
58.1%
/ 42
 
22.6%
. 36
 
19.4%
Math Symbol
ValueCountFrequency (%)
~ 29
96.7%
× 1
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7051
100.0%
Space Separator
ValueCountFrequency (%)
940
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69944
> 99.9%
Hangul 20
 
< 0.1%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11402
16.3%
2 10153
14.5%
- 7051
10.1%
5 5955
8.5%
7 5465
7.8%
1 5057
7.2%
3 4969
7.1%
6 4946
7.1%
8 4835
6.9%
4 4815
6.9%
Other values (10) 5296
7.6%
Hangul
ValueCountFrequency (%)
3
15.0%
3
15.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (6) 6
30.0%
Latin
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69945
> 99.9%
Hangul 20
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11402
16.3%
2 10153
14.5%
- 7051
10.1%
5 5955
8.5%
7 5465
7.8%
1 5057
7.2%
3 4969
7.1%
6 4946
7.1%
8 4835
6.9%
4 4815
6.9%
Other values (11) 5297
7.6%
Hangul
ValueCountFrequency (%)
3
15.0%
3
15.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (6) 6
30.0%
None
ValueCountFrequency (%)
× 1
100.0%

소재지
Text

MISSING 

Distinct8672
Distinct (%)89.4%
Missing298
Missing (%)3.0%
Memory size156.2 KiB
2024-05-11T15:47:45.245834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length31.500206
Min length15

Characters and Unicode

Total characters305615
Distinct characters619
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7938 ?
Unique (%)81.8%

Sample

1st row서울특별시 강남구 논현동 201번지 6호 노벨테크빌딩4층
2nd row서울특별시 강남구 역삼동 642-16 성지2차 509호
3rd row서울특별시 성동구 성수동2가 277번지 17호 성수아카데미타워
4th row서울특별시 중랑구 묵동 171-21 401호
5th row서울특별시 구로구 천왕동 176번지 골드프라자-305
ValueCountFrequency (%)
서울특별시 9699
 
17.0%
강남구 1663
 
2.9%
서초구 994
 
1.7%
역삼동 756
 
1.3%
1호 684
 
1.2%
송파구 619
 
1.1%
서초동 594
 
1.0%
중구 509
 
0.9%
2호 483
 
0.8%
영등포구 471
 
0.8%
Other values (9445) 40728
71.2%
2024-05-11T15:47:45.904149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67774
22.2%
1 13430
 
4.4%
12122
 
4.0%
11069
 
3.6%
10483
 
3.4%
9968
 
3.3%
9752
 
3.2%
9709
 
3.2%
9702
 
3.2%
2 8812
 
2.9%
Other values (609) 142794
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167395
54.8%
Space Separator 67774
22.2%
Decimal Number 63311
 
20.7%
Dash Punctuation 5430
 
1.8%
Uppercase Letter 1116
 
0.4%
Other Punctuation 232
 
0.1%
Close Punctuation 107
 
< 0.1%
Lowercase Letter 107
 
< 0.1%
Open Punctuation 103
 
< 0.1%
Letter Number 29
 
< 0.1%
Other values (2) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12122
 
7.2%
11069
 
6.6%
10483
 
6.3%
9968
 
6.0%
9752
 
5.8%
9709
 
5.8%
9702
 
5.8%
8621
 
5.2%
8510
 
5.1%
7973
 
4.8%
Other values (535) 69486
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 246
22.0%
A 212
19.0%
D 77
 
6.9%
S 75
 
6.7%
I 52
 
4.7%
T 48
 
4.3%
C 47
 
4.2%
K 46
 
4.1%
L 34
 
3.0%
E 31
 
2.8%
Other values (16) 248
22.2%
Lowercase Letter
ValueCountFrequency (%)
e 22
20.6%
n 15
14.0%
i 11
10.3%
r 8
 
7.5%
t 7
 
6.5%
l 7
 
6.5%
c 5
 
4.7%
s 5
 
4.7%
u 5
 
4.7%
a 5
 
4.7%
Other values (10) 17
15.9%
Decimal Number
ValueCountFrequency (%)
1 13430
21.2%
2 8812
13.9%
0 7910
12.5%
3 7049
11.1%
4 5822
9.2%
5 4864
 
7.7%
6 4591
 
7.3%
7 4160
 
6.6%
8 3337
 
5.3%
9 3336
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 93
40.1%
/ 80
34.5%
. 52
22.4%
4
 
1.7%
; 1
 
0.4%
# 1
 
0.4%
@ 1
 
0.4%
Letter Number
ValueCountFrequency (%)
19
65.5%
5
 
17.2%
5
 
17.2%
Math Symbol
ValueCountFrequency (%)
~ 8
80.0%
> 1
 
10.0%
< 1
 
10.0%
Space Separator
ValueCountFrequency (%)
67774
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5430
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Open Punctuation
ValueCountFrequency (%)
( 103
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 167394
54.8%
Common 136967
44.8%
Latin 1252
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12122
 
7.2%
11069
 
6.6%
10483
 
6.3%
9968
 
6.0%
9752
 
5.8%
9709
 
5.8%
9702
 
5.8%
8621
 
5.2%
8510
 
5.1%
7973
 
4.8%
Other values (534) 69485
41.5%
Latin
ValueCountFrequency (%)
B 246
19.6%
A 212
16.9%
D 77
 
6.2%
S 75
 
6.0%
I 52
 
4.2%
T 48
 
3.8%
C 47
 
3.8%
K 46
 
3.7%
L 34
 
2.7%
E 31
 
2.5%
Other values (39) 384
30.7%
Common
ValueCountFrequency (%)
67774
49.5%
1 13430
 
9.8%
2 8812
 
6.4%
0 7910
 
5.8%
3 7049
 
5.1%
4 5822
 
4.3%
- 5430
 
4.0%
5 4864
 
3.6%
6 4591
 
3.4%
7 4160
 
3.0%
Other values (14) 7125
 
5.2%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 167393
54.8%
ASCII 138186
45.2%
Number Forms 29
 
< 0.1%
None 5
 
< 0.1%
CJK 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67774
49.0%
1 13430
 
9.7%
2 8812
 
6.4%
0 7910
 
5.7%
3 7049
 
5.1%
4 5822
 
4.2%
- 5430
 
3.9%
5 4864
 
3.5%
6 4591
 
3.3%
7 4160
 
3.0%
Other values (59) 8344
 
6.0%
Hangul
ValueCountFrequency (%)
12122
 
7.2%
11069
 
6.6%
10483
 
6.3%
9968
 
6.0%
9752
 
5.8%
9709
 
5.8%
9702
 
5.8%
8621
 
5.2%
8510
 
5.1%
7973
 
4.8%
Other values (533) 69484
41.5%
Number Forms
ValueCountFrequency (%)
19
65.5%
5
 
17.2%
5
 
17.2%
None
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
CJK
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

소재지(도로명)
Text

MISSING 

Distinct4746
Distinct (%)91.5%
Missing4814
Missing (%)48.1%
Memory size156.2 KiB
2024-05-11T15:47:46.473649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length57
Mean length37.228114
Min length22

Characters and Unicode

Total characters193065
Distinct characters614
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4353 ?
Unique (%)83.9%

Sample

1st row서울특별시 성동구 성수이로 118, 성수아카데미타워 13층 1316호 (성수동2가)
2nd row서울특별시 종로구 종로 145-1 (종로3가)
3rd row서울특별시 강남구 논현로18길 14-15, 302호 (개포동, 에이스빌라)
4th row서울특별시 양천구 국회대로 252, 408호 (신정동)
5th row서울특별시 양천구 중앙로46길 31-3, 1층 (신정동)
ValueCountFrequency (%)
서울특별시 5186
 
14.1%
강남구 973
 
2.6%
서초구 596
 
1.6%
2층 454
 
1.2%
역삼동 441
 
1.2%
3층 387
 
1.1%
서초동 386
 
1.1%
영등포구 331
 
0.9%
송파구 322
 
0.9%
4층 310
 
0.8%
Other values (6602) 27365
74.5%
2024-05-11T15:47:47.178796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31588
 
16.4%
1 7335
 
3.8%
, 7132
 
3.7%
6911
 
3.6%
6727
 
3.5%
5707
 
3.0%
5704
 
3.0%
5395
 
2.8%
2 5331
 
2.8%
5242
 
2.7%
Other values (604) 105993
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107518
55.7%
Decimal Number 34338
 
17.8%
Space Separator 31588
 
16.4%
Other Punctuation 7147
 
3.7%
Close Punctuation 5236
 
2.7%
Open Punctuation 5234
 
2.7%
Dash Punctuation 1035
 
0.5%
Uppercase Letter 829
 
0.4%
Lowercase Letter 98
 
0.1%
Letter Number 27
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6911
 
6.4%
6727
 
6.3%
5707
 
5.3%
5704
 
5.3%
5395
 
5.0%
5242
 
4.9%
5195
 
4.8%
5188
 
4.8%
4238
 
3.9%
2681
 
2.5%
Other values (533) 54530
50.7%
Uppercase Letter
ValueCountFrequency (%)
B 167
20.1%
A 116
14.0%
S 71
 
8.6%
C 49
 
5.9%
T 45
 
5.4%
I 39
 
4.7%
K 37
 
4.5%
E 35
 
4.2%
L 31
 
3.7%
G 30
 
3.6%
Other values (15) 209
25.2%
Lowercase Letter
ValueCountFrequency (%)
e 19
19.4%
i 13
13.3%
n 12
12.2%
r 8
8.2%
t 7
 
7.1%
l 6
 
6.1%
c 5
 
5.1%
b 5
 
5.1%
s 3
 
3.1%
u 3
 
3.1%
Other values (10) 17
17.3%
Decimal Number
ValueCountFrequency (%)
1 7335
21.4%
2 5331
15.5%
0 4428
12.9%
3 4150
12.1%
4 2960
8.6%
5 2660
 
7.7%
6 2194
 
6.4%
7 1980
 
5.8%
8 1750
 
5.1%
9 1550
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 7132
99.8%
. 8
 
0.1%
@ 3
 
< 0.1%
? 2
 
< 0.1%
1
 
< 0.1%
/ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
17
63.0%
5
 
18.5%
5
 
18.5%
Math Symbol
ValueCountFrequency (%)
~ 13
86.7%
< 1
 
6.7%
> 1
 
6.7%
Space Separator
ValueCountFrequency (%)
31588
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5236
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5234
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1035
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107514
55.7%
Common 84593
43.8%
Latin 954
 
0.5%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6911
 
6.4%
6727
 
6.3%
5707
 
5.3%
5704
 
5.3%
5395
 
5.0%
5242
 
4.9%
5195
 
4.8%
5188
 
4.8%
4238
 
3.9%
2681
 
2.5%
Other values (530) 54526
50.7%
Latin
ValueCountFrequency (%)
B 167
17.5%
A 116
 
12.2%
S 71
 
7.4%
C 49
 
5.1%
T 45
 
4.7%
I 39
 
4.1%
K 37
 
3.9%
E 35
 
3.7%
L 31
 
3.2%
G 30
 
3.1%
Other values (38) 334
35.0%
Common
ValueCountFrequency (%)
31588
37.3%
1 7335
 
8.7%
, 7132
 
8.4%
2 5331
 
6.3%
) 5236
 
6.2%
( 5234
 
6.2%
0 4428
 
5.2%
3 4150
 
4.9%
4 2960
 
3.5%
5 2660
 
3.1%
Other values (13) 8539
 
10.1%
Han
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107514
55.7%
ASCII 85519
44.3%
Number Forms 27
 
< 0.1%
CJK 3
 
< 0.1%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31588
36.9%
1 7335
 
8.6%
, 7132
 
8.3%
2 5331
 
6.2%
) 5236
 
6.1%
( 5234
 
6.1%
0 4428
 
5.2%
3 4150
 
4.9%
4 2960
 
3.5%
5 2660
 
3.1%
Other values (57) 9465
 
11.1%
Hangul
ValueCountFrequency (%)
6911
 
6.4%
6727
 
6.3%
5707
 
5.3%
5704
 
5.3%
5395
 
5.0%
5242
 
4.9%
5195
 
4.8%
5188
 
4.8%
4238
 
3.9%
2681
 
2.5%
Other values (530) 54526
50.7%
Number Forms
ValueCountFrequency (%)
17
63.0%
5
 
18.5%
5
 
18.5%
CJK
ValueCountFrequency (%)
2
66.7%
1
33.3%
None
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

우편번호
Real number (ℝ)

MISSING 

Distinct1342
Distinct (%)30.3%
Missing5576
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean136242.23
Minimum3163
Maximum410762
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:47:47.409582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3163
5-th percentile110043.15
Q1132030
median135997
Q3142876
95-th percentile157030
Maximum410762
Range407599
Interquartile range (IQR)10846

Descriptive statistics

Standard deviation15480.35
Coefficient of variation (CV)0.11362373
Kurtosis51.991326
Mean136242.23
Median Absolute Deviation (MAD)4876
Skewness1.0992382
Sum6.0273561 × 108
Variance2.3964124 × 108
MonotonicityNot monotonic
2024-05-11T15:47:47.673148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135080 177
 
1.8%
137070 147
 
1.5%
135010 68
 
0.7%
157010 59
 
0.6%
152050 50
 
0.5%
151015 47
 
0.5%
151050 46
 
0.5%
158090 44
 
0.4%
130100 39
 
0.4%
142100 39
 
0.4%
Other values (1332) 3708
37.1%
(Missing) 5576
55.8%
ValueCountFrequency (%)
3163 1
 
< 0.1%
4526 1
 
< 0.1%
4534 1
 
< 0.1%
4538 1
 
< 0.1%
4554 1
 
< 0.1%
5510 1
 
< 0.1%
7327 1
 
< 0.1%
100011 3
< 0.1%
100012 2
< 0.1%
100015 2
< 0.1%
ValueCountFrequency (%)
410762 1
 
< 0.1%
410380 1
 
< 0.1%
158871 2
< 0.1%
158864 4
< 0.1%
158860 4
< 0.1%
158859 4
< 0.1%
158858 1
 
< 0.1%
158856 1
 
< 0.1%
158849 1
 
< 0.1%
158842 1
 
< 0.1%

등록일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3520
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20136681
Minimum20030519
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:47:47.931060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030519
5-th percentile20070906
Q120091209
median20130214
Q320170706
95-th percentile20230221
Maximum20240510
Range209991
Interquartile range (IQR)79497.25

Descriptive statistics

Standard deviation48740.259
Coefficient of variation (CV)0.0024204713
Kurtosis-0.88322208
Mean20136681
Median Absolute Deviation (MAD)39390
Skewness0.47348647
Sum2.0136681 × 1011
Variance2.3756129 × 109
MonotonicityNot monotonic
2024-05-11T15:47:48.142259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080814 34
 
0.3%
20080818 20
 
0.2%
20090611 20
 
0.2%
20090507 17
 
0.2%
20080731 16
 
0.2%
20081229 14
 
0.1%
20090619 14
 
0.1%
20080926 14
 
0.1%
20090330 13
 
0.1%
20090520 13
 
0.1%
Other values (3510) 9825
98.2%
ValueCountFrequency (%)
20030519 1
 
< 0.1%
20060306 1
 
< 0.1%
20060310 1
 
< 0.1%
20060320 2
< 0.1%
20060324 1
 
< 0.1%
20060329 1
 
< 0.1%
20060331 1
 
< 0.1%
20060407 1
 
< 0.1%
20060410 3
< 0.1%
20060411 1
 
< 0.1%
ValueCountFrequency (%)
20240510 2
< 0.1%
20240507 3
< 0.1%
20240503 2
< 0.1%
20240502 2
< 0.1%
20240430 1
 
< 0.1%
20240425 1
 
< 0.1%
20240424 4
< 0.1%
20240423 1
 
< 0.1%
20240422 2
< 0.1%
20240418 1
 
< 0.1%

유효기간만료일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3274
Distinct (%)41.1%
Missing2027
Missing (%)20.3%
Infinite0
Infinite (%)0.0%
Mean20180965
Minimum20091116
Maximum20270510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:47:48.405688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20091116
5-th percentile20120325
Q120141011
median20171215
Q320211213
95-th percentile20260512
Maximum20270510
Range179394
Interquartile range (IQR)70202

Descriptive statistics

Standard deviation44484.917
Coefficient of variation (CV)0.0022043008
Kurtosis-0.96470709
Mean20180965
Median Absolute Deviation (MAD)30600
Skewness0.3425831
Sum1.6090283 × 1011
Variance1.9789078 × 109
MonotonicityNot monotonic
2024-05-11T15:47:48.648153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140831 14
 
0.1%
20110831 13
 
0.1%
20141108 12
 
0.1%
20150426 11
 
0.1%
20190613 11
 
0.1%
20140808 11
 
0.1%
20140711 11
 
0.1%
20140615 10
 
0.1%
20160102 10
 
0.1%
20120330 10
 
0.1%
Other values (3264) 7860
78.6%
(Missing) 2027
 
20.3%
ValueCountFrequency (%)
20091116 1
< 0.1%
20100117 1
< 0.1%
20100219 1
< 0.1%
20100323 2
< 0.1%
20100326 1
< 0.1%
20100418 2
< 0.1%
20100419 1
< 0.1%
20100427 1
< 0.1%
20100501 1
< 0.1%
20100511 1
< 0.1%
ValueCountFrequency (%)
20270510 2
< 0.1%
20270507 3
< 0.1%
20270503 2
< 0.1%
20270502 2
< 0.1%
20270430 1
 
< 0.1%
20270425 1
 
< 0.1%
20270424 4
< 0.1%
20270423 1
 
< 0.1%
20270422 1
 
< 0.1%
20270421 1
 
< 0.1%

폐쇄일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3111
Distinct (%)37.0%
Missing1594
Missing (%)15.9%
Infinite0
Infinite (%)0.0%
Mean20141741
Minimum20050517
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:47:48.878617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050517
5-th percentile20090908
Q120110407
median20130719
Q320170412
95-th percentile20220925
Maximum20240510
Range189993
Interquartile range (IQR)60005.5

Descriptive statistics

Standard deviation40795.653
Coefficient of variation (CV)0.0020254283
Kurtosis-0.53625199
Mean20141741
Median Absolute Deviation (MAD)29792
Skewness0.69695799
Sum1.6931148 × 1011
Variance1.6642853 × 109
MonotonicityNot monotonic
2024-05-11T15:47:49.106547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091116 210
 
2.1%
20100927 64
 
0.6%
20110420 24
 
0.2%
20160725 23
 
0.2%
20111007 22
 
0.2%
20101213 20
 
0.2%
20110901 18
 
0.2%
20120420 16
 
0.2%
20101126 15
 
0.1%
20101228 15
 
0.1%
Other values (3101) 7979
79.8%
(Missing) 1594
 
15.9%
ValueCountFrequency (%)
20050517 1
< 0.1%
20060920 1
< 0.1%
20071030 1
< 0.1%
20071115 1
< 0.1%
20081212 1
< 0.1%
20090116 1
< 0.1%
20090219 1
< 0.1%
20090220 1
< 0.1%
20090305 1
< 0.1%
20090307 1
< 0.1%
ValueCountFrequency (%)
20240510 2
 
< 0.1%
20240507 2
 
< 0.1%
20240503 2
 
< 0.1%
20240502 1
 
< 0.1%
20240430 5
0.1%
20240429 1
 
< 0.1%
20240426 1
 
< 0.1%
20240423 1
 
< 0.1%
20240422 4
< 0.1%
20240419 1
 
< 0.1%

지점설립일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3536
Distinct (%)40.4%
Missing1246
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean20135072
Minimum19050627
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:47:49.358704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19050627
5-th percentile20070201
Q120100503
median20130403
Q320170413
95-th percentile20220510
Maximum20240510
Range1189883
Interquartile range (IQR)69910

Descriptive statistics

Standard deviation50070.619
Coefficient of variation (CV)0.0024867366
Kurtosis50.954225
Mean20135072
Median Absolute Deviation (MAD)30427
Skewness-2.2785833
Sum1.7626242 × 1011
Variance2.5070669 × 109
MonotonicityNot monotonic
2024-05-11T15:47:49.602566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090611 23
 
0.2%
20090520 21
 
0.2%
20090507 18
 
0.2%
20090820 18
 
0.2%
20090514 17
 
0.2%
20111108 15
 
0.1%
20090511 15
 
0.1%
20090528 15
 
0.1%
20100407 14
 
0.1%
20100524 14
 
0.1%
Other values (3526) 8584
85.8%
(Missing) 1246
 
12.5%
ValueCountFrequency (%)
19050627 2
< 0.1%
19660705 1
< 0.1%
19670425 1
< 0.1%
19940223 1
< 0.1%
19940418 1
< 0.1%
19950103 1
< 0.1%
19950501 1
< 0.1%
19950711 1
< 0.1%
19970301 1
< 0.1%
19970410 1
< 0.1%
ValueCountFrequency (%)
20240510 1
 
< 0.1%
20240502 1
 
< 0.1%
20240430 1
 
< 0.1%
20240425 1
 
< 0.1%
20240423 1
 
< 0.1%
20240422 1
 
< 0.1%
20240415 1
 
< 0.1%
20240411 3
< 0.1%
20240409 1
 
< 0.1%
20240408 2
< 0.1%

본점여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
본점
9928 
지점
 
72

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row본점
2nd row본점
3rd row본점
4th row본점
5th row본점

Common Values

ValueCountFrequency (%)
본점 9928
99.3%
지점 72
 
0.7%

Length

2024-05-11T15:47:49.779899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:49.915066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본점 9928
99.3%
지점 72
 
0.7%

최근수정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3184
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20152772
Minimum20090518
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:47:50.057657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090518
5-th percentile20091118
Q120110928
median20140806
Q320190327
95-th percentile20231020
Maximum20240510
Range149992
Interquartile range (IQR)79399.25

Descriptive statistics

Standard deviation45917.104
Coefficient of variation (CV)0.0022784511
Kurtosis-1.0507731
Mean20152772
Median Absolute Deviation (MAD)30477.5
Skewness0.4556377
Sum2.0152772 × 1011
Variance2.1083804 × 109
MonotonicityNot monotonic
2024-05-11T15:47:50.271604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091117 83
 
0.8%
20091118 55
 
0.5%
20090609 55
 
0.5%
20100927 46
 
0.5%
20100330 45
 
0.4%
20110425 39
 
0.4%
20130621 37
 
0.4%
20091116 34
 
0.3%
20090622 33
 
0.3%
20091119 31
 
0.3%
Other values (3174) 9542
95.4%
ValueCountFrequency (%)
20090518 2
 
< 0.1%
20090519 1
 
< 0.1%
20090521 1
 
< 0.1%
20090601 2
 
< 0.1%
20090602 2
 
< 0.1%
20090603 10
 
0.1%
20090604 15
 
0.1%
20090605 4
 
< 0.1%
20090608 5
 
0.1%
20090609 55
0.5%
ValueCountFrequency (%)
20240510 6
0.1%
20240509 2
 
< 0.1%
20240508 4
 
< 0.1%
20240507 10
0.1%
20240503 10
0.1%
20240502 6
0.1%
20240501 5
0.1%
20240430 7
0.1%
20240429 5
0.1%
20240426 1
 
< 0.1%

Interactions

2024-05-11T15:47:32.863797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:38.774210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:42.419359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:49.496134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:55.778145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:02.441840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:33.110801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:38.963124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:42.594344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:49.727292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:55.946088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:05.081843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:33.299196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:39.124683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:42.749691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:49.927779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:56.111334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:09.970071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:33.506585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:39.281489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:42.938810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:50.107086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:56.263909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:13.855862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:33.762539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:39.467278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:43.127249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:50.275675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:56.440113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:17.581760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:40.078957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:42.229102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:49.324916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:46:55.589674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:02.230619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:27.517115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:47:51.298398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업영업구분법인여부우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
등록신청사업1.0000.1130.0200.0200.1590.1500.2010.1420.0060.160
영업구분0.1131.0000.2970.0720.6360.6220.1840.2240.0710.545
법인여부0.0200.2971.0000.0490.2660.2900.2630.2900.1860.347
우편번호0.0200.0720.0491.0000.1650.1690.2420.0730.0000.254
등록일자0.1590.6360.2660.1651.0000.9640.8600.6630.0740.855
유효기간만료일자0.1500.6220.2900.1690.9641.0000.8450.6670.0780.841
폐쇄일자0.2010.1840.2630.2420.8600.8451.0000.6790.0770.985
지점설립일자0.1420.2240.2900.0730.6630.6670.6791.0000.0380.686
본점여부0.0060.0710.1860.0000.0740.0780.0770.0381.0000.108
최근수정일자0.1600.5450.3470.2540.8550.8410.9850.6860.1081.000
2024-05-11T15:47:51.465658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본점여부등록신청사업법인여부영업구분
본점여부1.0000.0040.1190.051
등록신청사업0.0041.0000.0120.081
법인여부0.1190.0121.0000.213
영업구분0.0510.0810.2131.000
2024-05-11T15:47:51.599778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호등록일자유효기간만료일자폐쇄일자지점설립일자최근수정일자등록신청사업영업구분법인여부본점여부
우편번호1.0000.0340.0130.0560.0540.0440.0080.0520.0250.000
등록일자0.0341.0000.9960.9590.9220.9650.1580.3780.2660.073
유효기간만료일자0.0130.9961.0000.9620.8930.9650.1150.3890.2230.059
폐쇄일자0.0560.9590.9621.0000.9000.9900.1540.1070.2020.059
지점설립일자0.0540.9220.8930.9001.0000.8920.1270.3050.3270.000
최근수정일자0.0440.9650.9650.9900.8921.0000.1230.3070.2660.083
등록신청사업0.0080.1580.1150.1540.1270.1231.0000.0810.0120.004
영업구분0.0520.3780.3890.1070.3050.3070.0811.0000.2130.051
법인여부0.0250.2660.2230.2020.3270.2660.0120.2131.0000.119
본점여부0.0000.0730.0590.0590.0000.0830.0040.0510.1191.000

Missing values

2024-05-11T15:47:40.324387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:47:40.650194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-11T15:47:40.938481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
24698대부업<NA>2010-서울강남-0422디비에스대부 유한회사법인07082465607서울특별시 강남구 논현동 201번지 6호 노벨테크빌딩4층<NA>13501020101224201312242011052520101224본점20110525
27117대부업<NA>2007-서울특별시-01327(대부업)성지대부개인025392063서울특별시 강남구 역삼동 642-16 성지2차 509호<NA>13508020071024<NA>2010090320071016본점20100910
5420대부업유효기간만료2018-서울성동-022(대부업)한울타리대부개인02-466-7706서울특별시 성동구 성수동2가 277번지 17호 성수아카데미타워서울특별시 성동구 성수이로 118, 성수아카데미타워 13층 1316호 (성수동2가)<NA>20180718202107192021071920180718본점20210805
24658대부중개업<NA>2008-서울특별시-01752(대부중개업)신성캐피탈개인02 948 1101서울특별시 중랑구 묵동 171-21 401호<NA><NA>200805282011052820110529<NA>본점20110531
17019대부중개업폐업2013-서울구로-018(대부중개업)새빛금융대부개인<NA>서울특별시 구로구 천왕동 176번지 골드프라자-305<NA>15213020130318201603182013123020130318본점20131231
10610대부업폐업2016-서울종로-00036(대부업)주)종로대부중개법인.<NA>서울특별시 종로구 종로 145-1 (종로3가)<NA>20161020201910202017052220161020본점20170523
26186대부업<NA>2009-서울특별시-01845(대부업)(주)효신기업대부법인<NA>서울특별시 서초구 양재동 275번지 4호 투윈타워빌딩 B동 223호<NA><NA>20090806<NA>2010121320090806본점20101213
13706대부업직권취소2014-서울강남-0068대산대부업개인02-501-5550서울특별시 강남구 개포동 1234번지 11호 에이스빌라-302서울특별시 강남구 논현로18길 14-15, 302호 (개포동, 에이스빌라)13596420140428201704282015111320140428본점20151118
16117대부업직권취소2013-서울양천-00024(대부업)소나무 대부개인<NA>서울특별시 양천구 신정동 897번지 5호 -408서울특별시 양천구 국회대로 252, 408호 (신정동)15807020130422201604222014060520130422본점20140605
30013<NA><NA>2007-서울특별시-00227현대개인64951698서울특별시 동대문구 장안동 319-3 신부아)201호<NA>13010020070213<NA>2009111620070202본점20091117
등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자
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29269대부업<NA>2009-서울특별시-00327(대부업)슈퍼스타개인<NA>서울특별시 마포구 상암동 1505<NA><NA>20090210<NA>20091229<NA>본점20091230
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25899대부업<NA>2008-서울특별시-01812(대부업)SH파이낸셜개인<NA>서울특별시 강북구 수유동 83-3<NA><NA>20080612<NA>20110113<NA>본점20110113
801대부중개업폐업2022-서울중구-0038(대부중개업)저스트 대부개인02-755-7779서울특별시 중구 명동1가 54번지 8호 개양빌딩-1401서울특별시 중구 명동3길 6, 개양빌딩 1401호 (명동1가)<NA>20221205202512052024020220221205본점20240206
24299대부업<NA>2010-서울마포-0118(대부업)e-클릭대부개인3143 0314서울특별시 마포구 성산동 251번지 4호 -201<NA>12125020101119201311192011071320101119본점20110713
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Duplicate rows

Most frequently occurring

등록신청사업영업구분등록증번호상호법인여부사업장 전화번호소재지소재지(도로명)우편번호등록일자유효기간만료일자폐쇄일자지점설립일자본점여부최근수정일자# duplicates
0대부업<NA>2009-서울특별시-02231(대부업)한빛투자금융대부개인025638488서울특별시 은평구 구산동 177번지 2호 명성골든빌 A-502호<NA><NA>20090918<NA>2010021120090918본점201006042